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Fuzzy Logic - artificial intelligence:
In the above logic, we have been concerned with truth whether propositions and sentences are true. But, with some natural language statements, it is difficult to assign a "true" or "false" value. For instance, is the sentence: "Prince Charles is tall" true or false? Some people may say true, and others may say false, so there is an underlying probability that we might also want to represent. This can be attaining with so-called "fuzzy" logics. As such, the originator of fuzzy logics, Lotfi Zadeh, advocates not thinking about specific fuzzy logics but rather thinking about "fuzzification" of current theories, and this is starting to play a part in Artificial Intelligence. The arrangement of logics with programming agents and theories of probability to reason in the light of uncertain knowledge are important areas of Artificial Intelligence research. Various representation schemes such as Stochastic Logic Programs have an aspect of both logic and probability.
DATA SEGMENT NUM1 DB 15h; First number NUM2 DB 20h; Second number RESULT DB? ; Put sum here CARRY DB? ; Put any carry he
This comes at the complication time, If we give the LOGO option to the compiler, it take a bitmap file (i.e., ) as logo previous to loading the Application.
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a ship is loaded with a stock of 3 items each unit of item n has a wt wn and vn the max cargo wt the ship can take is the details of 3items are item(n):1 2 3 wt(wn):2 3 1 value(vn)
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